The present invention relates to a system and method for transforming multi-sensor data from its measurement coordinates into display grids designed for human display and, more particularly, to a system and method for interpreting and analyzing multi-sensor data.
Conventional sensors that create 4-dimensional data include radar, sonar, LIDAR, and many types of medical sensors. These sensors collect data as a series of 1-dimensional rays through the environment as a function of time. Typically, in these conventional systems, a series of such arrays of measurements are made at closely-spaced points in time where each array of measurement is made in a coordinate system determined by the position and orientation of the sensor at the time the measurement is made. Such data can be difficult to interpret in its raw form because the data is often collected in a polar or spherical coordinate system, and because, the sensor""s position and/or orientation cannot be precisely controlled at the instant of measurement. The problem of data analysis and interpretation is further compounded by the fact that the sensor""s position changes with time. Furthermore, multiple sensors in different locations may provide data each having different characteristics.
Because modern sensors have the ability to collect large numbers of observations per second, there currently exists a need for a system and method to filter the large volume of raw data, determine which parts of the data are needed for a particular display, extract only these relevant portions for processing, and, finally, to display data for interpretation in the observer""s chosen coordinate system.
It is accordingly an object of the present invention to provide a system and method that can enable an operator to specify what data is of interest and use that specification to process only the data required to synthesize the requested display.
It is another object of the invention to allow historic data and data from multiple sensors to be used to satisfy the operator""s display requirements thus obviating the need for additional data measurements by the sensors and allowing more of the sensor""s duty cycle to be made available for additional uses.
Operationally, the invention described herein and shown in FIGS. 1-13 has many benefits and advantages over conventional systems. In particular, most sensors in conventional systems lack the ability to measure data in a format that directly suits an operator""s needs. For example, radar measures data in a polar or spherical coordinate system with the origin at the radar""s current spatial location. Each sweep of the radar antenna is considered to be a frame of data. In one embodiment of this invention, the operator requires a Cartesian PPI (Plan Position Indicator) for use in planning a navigation strategy. Each radar pulse in the sweep produces an array of data corresponding to range gates out to a maximum range along a 1-dimensional line-of-sight. Generally, one frame of data cannot fill a regular Cartesian grid such as horizontal slice at a constant altitude. Even with an electronically scanned antenna, it is difficult and inefficient use of the sensor""s time line to measure explicitly vertical or horizontal slices. Using this method and apparatus, multiple polar sweeps would be taken and then transformed into as many independent planar slices as desired.
Continuing with the example of airborne weather radar as the embodiment of this invention, where the returns from individual pulses from the radar are measurements of power as a function of range, where range is quantified into discrete cells. Each individual return corresponds to a line of sight, or ray, along which the antenna""s main lobe is assumed to point and along which the measured targets are assumed to lie. Typically, each such ray has a direction specified by the azimuth and elevation of the ray in the coordinate system determined by the position and attitude of the aircraft at the time the measurement was made.
For many sensor systems (i.e., radar), the rays can be considered to follow essentially straight-line paths. However, many propagation media exhibit refraction or diffraction effects that can cause the rays to deviate from straight lines. As long as there is a deterministic way to characterize this bending, the current invention permits even curved ray paths to be used.
A collection of such rays can be grouped into a frame. In the example of a weather radar with a mechanically scanned antenna, the collection of rays taken during a single scan of the radar with a constant measurement basis makes a logical grouping for a frame. In other instances, other groupings may be more appropriate. In grouping a collection of rays into a frame, it is useful to maintain them in a common local coordinate system. In the case of the aforementioned radar, a logical choice is the coordinate system of the first pulse in the scan. Because this is known at the beginning of the scan, the subsequent pulses can be converted to this coordinate system in real time, as they arrive. This coordinate transformation is determined by the position and orientation of the radar at the time of the measurement and is different for each pulse. In the case of fixed (e.g. ground-based) radar, no coordinate transformation may be necessary.
Once the data is collected into frames, the frames may be saved in a frame database from which they may be accessed for subsequent processing and display. Note that while the individual measurements within a frame have been translated to a common coordinate system within the frame, each frame is stored in the database in a coordinate system that is specific to that individual frame.
The user may access the data in the frame database for subsequent processing or to generate displays. In the example of weather radar, one way in which the data may be accessed is in generating a horizontal or vertical planar slice through the 3-dimensional volume of space being measured. Another way in which the data may be accessed is in generating a voxel image of a 3-dimensional volume of space. Such methods may request data along a regular grid of points in a coordinate system that is independent of the coordinate systems in which the individual frames are stored. Note that the regular grid of points may be in any arbitrary orientation and need not be aligned with any horizontal or vertical.
Ray coordinates from each collection system frame are first transformed from their local measurement coordinate system into the planar grid coordinate system. In this common coordinate system, the ray coordinates are then transformed into a grid analysis space such that the image grid plane is in the x-y plane, and distance out of plane is the z dimension. This is implemented using a single coordinate transformation.
In a typical application, data collected over time by one or more sensors is measured in many different spatial coordinate systems. This can be due to the inherent motion of the sensor itself, or an inability to control the sensor""s position to within the measurements spatial precision. Also, when studying the evolution of spatial data in a sequence of displays or data extraction operations, the desired output coordinate system changes continuously. To be useful, data from all relevant measurement frames considered by a human operator or computer algorithm in a single analysis must ultimately be transformed into a single spatial coordinate system. This method implements a sequence of transformations which utilize each individual data frame""s measurement coordinate systems and the desired output spatial system to efficiently implement the coordinate conversions.
After applying the coordinate transformations and quantization of the data to the analysis grid, the method can utilize the time (history) dimension to analyze short-term time dependent phenomena and suppress measurement noise. The method also produces indications of which grid cells have not been measured by any sensor system during the time interval and contain no sensor information. This information may be used in the scheduling of subsequent measurements. The efficiencies of: 1) storing the data in the individual frame coordinate systems, and 2) retrieving only the data needed to fill the requested coordinate grid, permit such processing to take place in real time in situations where less efficient processing may have precluded real time functioning.
The disclosed invention further relates to the transformation of data sampled at discrete points through a 3-dimensional sample volume as it evolves over time. The sensor""s position and orientation sample the space through a coordinate system translated and rotated from the orientation of the intended display coordinate system. This is typically the case for radar systems onboard aircraft, surface ships, and spacecraft where the orientation of the craft is dynamically changing as a function of time. This is also applicable to other sensor systems including LIDAR, sonar and infrared systems on a variety of moving platforms. For a Radar, LIDAR or sonar sensor, range samples of the data are collected as the sensor scans in azimuth and/or elevation. Due to the translation over time and the interaction of the platform with the physical world, each scan is typically not coincident with any other scan nor is it consistent with the desired display coordinates.
Present day airborne weather radar systems present weather information to the pilot as a Planned Position Indicator (PPI) display. A PPI display is a polar presentation form that indicates signal return strength as a function of range and angle from the sensor platform. The weather radar is typically used to scan at elevation tilt angles, selected by the radar operator, to best observe the current weather conditions. Since the current weather radar""s have elevation beam widths ranging from 3xc2x0 to 8xc2x0, each scan of the radar provides a narrow scan through the 3-D volume of weather.
In the first implementation, multiple scans of the radar, each scan being at a different antenna tilt angle and each scan""s origin being translated from the previous based on the aircraft""s velocity and time between transmitted samples taken during the scan, are collected into a database of radar reflection data. To display multiple radar scans on the same display, the data must be translated and rotated into a common coordinate system consistent with the display coordinates. A number of U.S. patents have approached this problem by translating, rotating and spatially quantizing data into voxels in 3-space. Since weather radar"" data typically covers ranges out to 320 nmi, and cover a scan angle of 180xc2x0, a database made up of voxels on the order of the size of typical weather features would be enormous. Also, since the voxels contain information from multiple scans, there is no direct way to remove aging weather information from the database. Generating generalized slices through the 3-D space defined in voxels requires another rotation adding even more quantization to the final display image. Also, no mechanism is provided to discriminate voxels that have been examined yet contain no reflected energy versus those that have not been examined. The disclosed invention solves other practical implementation issues of the prior art by defining a 3-D weather database and generalized slicing display mechanism.
As is described in greater detail below, this means and apparatus are expected to serve in a number of applications. Real time generation of multi-planar images of multi-source weather data for airplane navigation is one good application. This detail description will focus on how the invention serves to meet that need. Other applications follow by implication.
In accordance with one embodiment of the invention, an apparatus for transforming data into planar grid for display for use in an airborne weather radar system is disclosed, where the apparatus comprises: a plurality of sensors for collecting data; a frame generator which receives data collected by the sensors and transforms the data into individual data frames for further processing; a database which receives the data frames from the frame generator; an input device for receiving requests from a user for a planar grid of interest; a CPU which, in response to instructions received from the input device, (i) requests data frames of interest from the database for display, (ii) transforms the data frames of interest to a common coordinate system, (iii) filters the data frames of interest for relevance to the planar grid of interest, and (iv) marks data frames identified as relevant; and a display for presenting the planar grid of interest based on the data frames marked as relevant.
In accordance with another embodiment of the invention, a method for transforming data into a planar grid for display for use in an airborne weather radar system is disclosed, where the method comprises the steps of: collecting data from a plurality of sensors; transforming the data into individual data frames for further processing; storing the data frames in a database; receiving a request from a user for a planar grid of interest; requesting data frames of interest from the database for display; transforming the data frames of interest to a common coordinate system; filtering the data frames of interest for relevance to the planar grid of interest; marking the data frames identified as relevant; and displaying the data frames marked as relevant on a planar grid.